We are building out an AI team in Toronto and are hiring Senior Machine Learning Engineers. This is a build-from-scratch effort on a modern stack, focused on putting AI into production rather than keeping it in the lab. You will work hands-on with LLMs, agentic and multi-agent systems, retrieval-based architectures, and current MLOps practices on a major cloud platform.
This is an early-stage seat on a team that is just forming, so there is real room to influence how things get built and to set technical direction rather than inherit it. They want a hands-on senior engineer who prefers to stay technical rather than move into people management, someone who has shipped ML/AI systems that real users depend on and enjoys working through open-ended problems. You get the independence to make real technical calls, the right resources behind you, strong visibility and a clear path toward Lead or Principal level.
Required Skills & Experience
- 7+ years building production ML/AI systems
- Strong hands-on Python and modern ML frameworks (PyTorch)
- Hands-on generative AI experience: LLMs, retrieval-based architectures, agentic workflows
- Track record of taking ML systems from prototype to production at scale
- Production ML engineering: MLOps, containerization (Docker, Kubernetes), cloud (AWS or Azure), workflow orchestration (Airflow), API development (FastAPI)
- Solid software fundamentals: automated testing, version control, scalable architecture
- Comfort leading through technical influence and mentorship rather than direct management
- Bachelor's in CS, Machine Learning, Data Science, Applied Math, or related field
Desired Skills & Experience
- Master's or PhD
- Multi-agent or agentic systems built beyond basic LLM integrations
- Advanced MLOps and cloud-native ML infrastructure at scale
- Experience with unstructured data
- Open source contributions, talks, or published work
- Early-stage or 0-to-1 team experience
What You Will Be Doing
Tech Breakdown
- 40% Generative AI and Agentic Systems (LLMs, retrieval, multi-agent)
- 30% Production ML Engineering and MLOps
- 30% Architecture and System Design
Daily Responsibilities
- 80% Hands On
- 20% Team Collaboration
The Offer
- Bonus eligible
You Will Receive The Following Benefits
- Medical, Dental, and Vision Insurance
- Vacation Time
Current Vacancy: Yes
Use of AI in Hiring: No
Applicants must be currently authorized to work in the Canada on a full-time basis now and in the future.
Posted By: Seif Tadros